Prozessvorhersage und maschinelles Lernen

Modulnummer: Q06-25
Englischer Titel: Process prediction and machine learning
Leistungspunkte: 6
Lehrperson: Revoredo

Empfohlene Vorkenntnisse

Grundlagen des Geschäftsprozessmanagements

Zwingende Voraussetzungen

keine

Inhalt

The digitization of the processes of an organization has made available a vast amount of trace data about the execution of these processes, which allows for the use of data-driven process monitoring techniques such as process prediction. Business process prediction involves learning a predictor from data with the aim of forecasting specific details, such as the next activity to be executed, the time remaining for the completion of a process instance, or key process indicators, for an ongoing process instance. This course focuses on recent developments in business process prediction, covering or touching upon topics such as data pre-processing, machine learning, process mining, process monitoring, process prediction, and evaluation methodology. In a mixture of theoretical, and hands-on sessions, students will be able to gain a deeper understanding of the area of process prediction.

The lectures are complemented with exercises, in which students will work on a project that takes up state-of-the-art developments in the field to collect, pre-process, analyze process data, and to use this data to learn prediction models. The results must be presented by the end and written up in a report.

Erforderliche Arbeitsleistungen für LP-Vergabe und Prüfungszulassung

- development and presentation of the project

Lehrveranstaltungen

Vorlesung: 2 SWS 3LP
Übung: 2 SWS 2LP
MAP: 1LP

Zugeordneter Vertiefungsschwerpunkt

Algorithmen und Modelle: nein
Modellbasierte Systementwicklung: nein
Daten- und Wissensmanagement: ja
Ohne Vertiefungsschwerpunkt: nein

Sprache im Modul

Deutsch: nein
Englisch: ja

Angeboten für Studiengänge

M. Sc.: ja
M. Ed.: ja
Wirtschaftsmaster: ja

Angeboten im

Wintersemester: ja
Sommersemester: nein

Turnus

Jedes Jahr